Biology subjects

Widge, A. S.

Publications and source records attributed to Widge, A. S..

At least 19 recordsLinked to original sources

bioRxiv2026

In silico optimization of deep brain stimulation to enhance cognitive control: Improving performance and practicality with a continuous rolling arena

Abstract Objective. Deep Brain Stimulation (DBS) of the ventral capsule/ventral striatum (VCVS) offers therapeutic potential for refractory psychiatric conditions, but clinical success is hindered by time-consuming, trial-and-error parameter programming reliant on subjective self-reports. Tracking objective behavioral markers allows contact settings to be evaluated rapidly. Here, we evaluate a direct closed-loop Multi-Armed Bandit (MAB) optimization framework designed to rapidly identify optimal stimulation contacts using raw reaction time (RT) during a cognitive control task. Approach. We leveraged empirical data demonstrating that VCVS DBS enhances cognitive control during the Multi-Source Interference Task (MSIT) in a site-specific manner. Using a synthetic patient simulation environment across 1,000 replicates, we benchmarked adaptive MAB algorithms under noisy, non-stationary conditions. Crucially, we eliminated intermediate state-space sensor models to evaluate raw RT directly, transitioned from discrete daily resets to an uninterrupted continuous optimization architecture, and implemented a rolling arena mechanism to scale contact selection under real-world hardware constraints. Main results. Eliminating the intermediate sensor model prevented high-frequency noise amplification (where state variance was inflated by 51.7% in baseline and 148.0% in conflict states) and reduced contact ranking failure rates from 31.9% down to 11.9%. Operating within a continuous trial architecture preserved historical sample density, driving mean trial-level regret down steadily over 4,200 trials and enabling dynamic re-convergence across unannounced mid-session change-points. Additionally, a 4-contact sub-arena successfully scaled search efficiency across 8-contact arrays without sacrificing selection accuracy. Significance. Direct MAB optimization within a continuous rolling arena provides a noise-resilient, hardware-compatible architecture for automated DBS programming. By bypassing latent state estimation and utilizing standard task-based behavioral metrics without specialized recording hardware or complex state-space modeling, this framework reduces search timelines to clinically feasible durations, establishing a scalable foundation for real-time, patient-tailored neuromodulation.

neuroscience↗

bioRxiv2026

Prefrontal cortical pathways mediating cognitive control enhancement from internal capsule stimulation

BackgroundDeep brain stimulation (DBS) targeting the ventral internal capsule/ventral striatum (VCVS) is an effective treatment for several psychiatric disorders, but clinical responses often vary amongst patients likely due to an incomplete mechanistic understanding of the brain pathways mediating response. VCVS DBS can improve cognitive control, a core deficit in multiple psychiatric disorders. Here, we investigated which prefrontal cortical pathway(s) in the internal capsule are associated with improving cognitive control during VCVS DBS. MethodsFour participants with bilateral VCVS DBS completed the Multi-Source Interference Task (MSIT) under 27 stimulation settings varying by side (left/right lead), electrode, amplitude, and frequency. Each condition included 100 trials and response time (RT) assessed task performance. Personalized pathway activation models quantified axonal recruitment across 11 segmented prefrontal cortical fiber bundles per brain hemisphere. Associations between pathway activation and task RT were analyzed to identify circuits linked to improved cognitive control performance. ResultsRight-sided VCVS stimulation produced greater improvements in cognitive control (reductions in MSIT RT) than left-sided stimulation. Activation of right dorsal prefrontal cortical pathways connected to the dorsolateral prefrontal cortex (dlPFC) and dorsomedial prefrontal cortex (dmPFC) most strongly predicted faster MSIT RTs, whereas no left-sided pathways were associated with performance changes. ConclusionsThese findings suggest that the effects of VCVS DBS on cognitive control are primarily mediated by right dorsal prefrontal cortical axons projecting from the dlPFC and dmPFC. Targeting these pathways may improve stimulation strategies and outcomes for psychiatric disorders characterized by impaired cognitive control.

neuroscience↗

bioRxiv2026

mPFC axons drive cognitive control enhancement during striatal stimulation

Deep brain stimulation (DBS) of the ventral internal capsule/ventral striatum (VCVS) can alleviate symptoms of mental illness and may work in part by improving cognitive control, a feature of healthy decision making. The human VCVS DBS target and its mid-striatum analog in our preclinical rodent model contain both cortical axons and local striatal cell bodies. However, the specific neural components that stimulation acts on to mediate cognitive effects remain unclear. We addressed this by delivering high frequency optogenetic stimulation ("opto-DBS") to either medial prefrontal cortex (mPFC) axons or local mid-striatal (midSTR) neurons in a rodent Set-Shift task. Opto-DBS of mPFC axons reduced response times, effectively replicating the cognitive enhancement observed in a previous study that used electrical stimulation. Conversely, we observed cognitive impairment from sustained (>10 min) opto-DBS of midSTR neurons. In addition, the cognitive benefit from axonal opto-DBS exhibited time-dependent declines that were not observed with electrical stimulation. The improvement in response times declined within a session and was associated with attenuated magnitude of local midSTR evoked-response potentials. Across-testing days, we linked this decline to diminished mPFC responsiveness, evidenced by a reduction in the post-DBS functional strength of the circuit, suggesting a neuroplastic-like mechanism. These results demonstrate that mPFC-originating axons, rather than local neurons, are the primary drivers of cognitive control enhancements from electrical stimulation, providing insight into therapeutic mechanisms of VCVS DBS.

neuroscience↗

bioRxiv2025

Real-time Bayesian optimization of deep brain stimulation for personalized cognitive control enhancement

BackgroundIdentifying effective deep brain stimulation (DBS) parameters for psychiatric disorders has historically been a time-consuming and error prone process due to a lack of an objective and rapid readout of target circuit engagement. Cognitive control may have use as a biomarker of treatment efficacy but it has yet to be shown that DBS parameters can be reliably optimized to produce cognitive control improvements in individual subjects. ObjectiveWe sought to leverage a rat model of DBS-driven cognitive control improvements to determine whether state of the art optimization algorithms could consistently identify effective stimulation amplitudes to enhance cognition. MethodsWe delivered periods of active and inactive DBS-like stimulation at variable parameters while rats performed a Set-Shifting task that we previously showed to be stimulation-sensitive. We tested both predefined settings of interest and settings that were personalized to individual animals using Bayesian Optimization. Measurements of task performance including reaction time and accuracy were compared between acute, optimized, and traditional settings to evaluate effects on cognitive control. ResultsAcute stimulation reduced reaction times without hindering accuracy (N=15), replicating the effects previously observed with chronic stimulation. In a second cohort (N=6), optimization of stimulation amplitude successfully reduced reaction times in all animals with comparable effect size to historically best settings. ConclusionThese findings confirm that optimization techniques can be effective for improving symptomatically-relevant cognitive markers supporting the feasibility of personalized, quantitatively-informed approaches to neuromodulation and target engagement for psychiatric and/or cognitive disorders. HighlightsProving target engagement is a substantial challenge across brain stimulation modalities, and objective, rapid behavioral read-outs may be a solution to that challenge. Reaction times in cognitive control tasks are an example of a behavioral measure that changes rapidly in response to changes in stimulation parameters, and that also may predict clinical outcomes. Individually optimal stimulation amplitudes for reducing reaction time by stimulating corticofugal fibers passing through the striatum can be determined using Bayesian Optimization. Individually optimized settings discovered in an acute preparation demonstrate consistent effects when applied chronically.

neuroscience↗

bioRxiv2025

Cognitive state dependent enhancement of cognitive control with transcranial magnetic stimulation

BackgroundRepetitive transcranial magnetic stimulation (rTMS) is an effective treatment for major depressive disorder (MDD), yet variability of therapeutic responses remains high. A key contributor to this variability may be state-dependent effects of brain stimulation, where activity in underlying circuits can shape the propagation of TMS-evoked activity. Thus, constraining the target circuits state by engaging cognition may make TMS effects more consistent. ObjectiveWe tested whether TMS effects on cognitive control, a transdiagnostic construct implicated across psychiatric disorders and a putative mediator of TMS efficacy, are state-dependent. MethodsParticipants (N = 25) completed a context-dependent behavioural assay of cognitive control before and after we delivered rTMS to the prefrontal cortex (PFC). During rTMS, participants performed either the cognitive control task (active-state TMS), or performed a context-independent perceptual task (control-state TMS). We assessed changes in downstream behavioural metrics of circuit function, as well as neural indices of cognitive control measured from electroencephalography (EEG). ResultsrTMS enhanced downstream readouts of cognitive control only when stimulation was delivered concurrent with the cognitive control task. Similarly, only active-state TMS modulated theta band oscillatory activity, which is thought to be a marker of cognitive control engagement ConclusionThese findings demonstrate that TMS effects on cognitive control are state-dependent, in which endogenous engagement of PFC-anchored networks can shape the magnitude and functional relevance of TMS-induced plasticity. Considering cognitive states during TMS may therefore offer a framework to enhance and/or accelerate TMS therapeutic effects.

neuroscience↗

bioRxiv2025

Unilateral striatal deep brain stimulation improves cognitive control

Deep brain stimulation (DBS) of the ventral capsule/ventral striatum (VCVS) can treat obsessive-compulsive disorder (OCD) and other psychiatric conditions. Yet, optimizing its clinical efficacy is a major challenge, often hindered by incomplete knowledge of how stimulation parameters and targets affect neural activity and behavior. VCVS DBS is thought to work in part by improving cognitive control, an important decision-making component that is impaired in OCD and other illnesses. The magnitude of this cognitive control enhancement was shown to be lateralized, with right-unilateral stimulation being the most effective. Prior work developed a preclinical model of VCVS DBS by leveraging the cognitive control construct, which can be measured in humans and rodents and is modulated by analogous brain circuits. However, this work did not address laterality effects observed in humans or examine left/right stimulation differences. These effects may be critical for maximizing therapeutic benefit while avoiding aversive outcomes. This study aimed to investigate lateralization in the rodent model, where bilateral stimulation of the mid-striatum was previously shown to improve cognitive control. Right and left-unilateral stimulation reduced response times without changing accuracy, replicating the cognitive control improvement from bilateral stimulation. With computational modeling, we show that bilateral and unilateral stimulation modifies the same decision-making variables to drive this behavior change. We also establish that females have the same cognitive control improvement from stimulation as males. These findings increase our understanding of cognitive control circuits and strengthen the validity of the rodent model as a translational platform to study VCVS DBSs therapeutic mechanisms. Significance StatementHere, we demonstrate that stimulating just one side of the brain (e.g. unilaterally) can be as effective as bilateral stimulation for improving cognitive control, the ability to adjust thoughts and decisions in response to environmental changes. These findings in rodents match results from prior human deep brain stimulation (DBS) studies, highlighting the validity of this preclinical model to study DBSs therapeutic mechanisms. We hypothesize that unilateral stimulation may be preferable to maximize cognitive benefits without causing off-target effects, while also reducing surgical invasiveness. Further, we demonstrate that females have the same cognitive control improvement from stimulation as males. Overall, this work answers important outstanding clinical questions regarding laterality and sex in DBS therapies for psychiatric illnesses.

neuroscience↗

bioRxiv2025

Cingulate-centered flexible control: physiologic correlates and enhancement by internal capsule stimulation

Flexible cognitive control requires rapid adjustment when current demands diverge from the brains predictions. Deficits in control adjustment are prominent in psychiatric disorders, yet the neural mechanisms supporting such adjustment and their modifiability remain unclear. We analyzed two intracranial electroencephalography datasets, one with brief internal capsule stimulation (ICS), to identify a human circuit mechanism for flexible adjustment after control-demand change. We further used two clinical internal capsule deep brain stimulation (IC DBS) cohorts to validate our proposed mechanism. Across intracranial datasets, phase-amplitude coupling (PAC) anchored to the theta phase of right rostral anterior cingulate cortex (rACC-R), particularly theta-gamma coupling with dorsolateral prefrontal cortex and dorsal ACC, was associated with faster performance specifically when control demand changed. This effect generalized across datasets and tasks and was robust across analytic pipelines. An adaptive drift-diffusion model accounted for this adjustment cost in terms of unsigned control prediction error. In Dataset 1, brief ICS selectively enhanced the same rACC-R theta-centered PAC configuration on control-state-change trials, and computational modeling indicated that stimulation improved control flexibility under high-mismatch conditions. In a primarily treatment-resistant depression IC DBS cohort, stimulation-induced enhancement of the flexibility-related behavioral parameter, rather than a more general-control parameter, was associated with clinical response (N = 14; AUC = 0.90). In a separate treatment-resistant obsessive-compulsive disorder IC DBS cohort, clinically selected stimulation settings preferentially increased the same flexibility-related parameter across all patients (N = 5). These findings identify rACC-centered theta-phase coordination as a candidate human mechanism for flexible adjustment, show that capsule stimulation can augment this mechanism when flexibility is required, and suggest a causal link between flexibility-related behavioral and neural signals and psychiatric symptoms.

neuroscience↗

bioRxiv2025

Sex Based Differences in Active Avoidance and Approach Strategy in the Platform Mediated Avoidance Task

Sex differences have been documented in threat conditioning, but research into potential sex differences in avoidance paradigms, particularly active avoidance, remains limited. This research gap is particularly concerning given that women are disproportionately affected by stress- and anxiety-related disorders, characterized by maladaptive avoidance. Yet, preclinical research has historically focused on male subjects, limiting our understanding of the neurobiological mechanisms underlying sex differences in threat responses. To address this, we investigated sex-specific strategies in adult Long Evans rats (10 female, 9 male) using a modified platform-mediated avoidance (PMA) task that created a high-conflict choice between reward-seeking and safety. Behavior was tracked over 25 days, with analyses focusing on a stable performance phase (days 20-25) objectively defined using change point analysis. The study design included an initial cohort and a replication cohort to ensure the findings robustness. Females consistently prioritized safety, spending significantly more time foregoing reward to avoid foot shock, while males engaged in more persistent reward-seeking despite the risk of shock. This difference was not driven by differential reward motivation. Furthermore, female strategies were not significantly modulated by the estrous cycle. Thus, male and female rats employ fundamentally different strategies to resolve approach-avoidance conflict: females adopt a robust, safety-first strategy, while males demonstrate a risk-prone, reward-oriented approach. These findings highlight the importance of considering biological factors underlying threat responses, suggesting that characterizing these neural mechanisms may guide more targeted interventions for anxiety and trauma-related disorders.

animal behavior and cognition↗

bioRxiv2025

NeuroTest: a benchtop testbed for evaluating sensing-capable electrophysiology and neurostimulation systems

ObjectiveThe development of increasingly complex implantable neuromodulation devices requires extensive benchtop validation and testing prior to in vivo implementation. Our goal is to enable this in vitro testing by creating a benchtop system that is accessible, easy-to-use, and functions reliably across academic and industry environments, reducing discordant results that arise from discordant approaches. Furthermore, such a system paves the way for standardizing benchtop characterization of future implantable systems by establishing a repeatable and comparable methodology for validating these devices and their capabilities. ApproachWe describe the NeuroTest Board (NTB), a low-cost, open-source device that combines a low-noise current source waveform generator with a high-precision data acquisition system. We provide information on its architecture, operation, and performance as an initial benchmark of the potential capabilities of the system. Main resultsWe demonstrate the use of the NTB to assess electrophysiology systems in two separate applications. In one case, we assess a commonly used laboratory system (the RHD2132 headstage and Open Ephys data acquisition system), while the second case characterizes an investigational neuromodulation device in development for human use (the CorTec Brain InterChange). Following this initial sensing characterization, we explore stimulation-related artifacts that would hamper in vivo data collection. With the NTB, we develop and evaluate artifact mitigation strategies for each system, thus demonstrating an example application of this benchtop testbed. SignificanceThe ability to test neuromodulation devices against a common benchmark will enable faster development of novel therapeutics by increasing inter-institutional reliability and decreasing troubleshooting time.

bioengineering↗

bioRxiv2025

Sex-biased computations underlying differential set shift performance in mice

Cognitive flexibility can be defined as the ability to adaptively shift between choices or strategies based on environmental feedback and it is disrupted in numerous neuropsychiatric conditions. Individual differences in the computations supporting cognitive flexibility are poised to reveal mechanisms of neuropsychiatric risk and resilience. One critical variable well known to influence individual differences in neuropsychiatric risk is sex. While previous research has identified sex differences in value based decision making in mice, whether sex reflects a major source of variation in cognitive flexibility remains unknown. To directly assess sex-biased individual differences in cognitive flexibility, we developed a novel touchscreen Set Shift task that permits robust and continuous testing in mice. Using this task, we discovered that female mice completed significantly more rule shifts with fewer errors than males. We next employed a suite of computational models that revealed sex-biased individual differences in the computations underlying cognitive flexibility. Overall, our results suggest that following rule shifts, female mice learn the new rule faster and commit to exploiting rule choices sooner compared to males - sometimes because they commit to multiple rules simultaneously. This suggests that increased choice stability in female rodents enhances commitment to a strategy during periods of uncertainty and directly contributes to increased rule shifting. This supports the counterintuitive conclusion that a high degree of stable choice is a strong requirement for enhanced cognitive flexibility in the Set Shift task, one of the gold standard cognitive flexibility tasks.

animal behavior and cognition↗

bioRxiv2024

Sequential estimation of nonstationary oscillator states and stimulus responses

Neural oscillations have been linked to multiple behaviors and neuropsychiatric disorders. The individual contributions to behavior from both oscillations and non-oscillatory activity are still unclear, complicating efforts to link neurophysiology to cognition, hindering the discovery of novel biomarkers, and preventing the development of effective therapeutics. To overcome these hurdles, it will be critical to investigate the biological origins of neural oscillations by characterizing the dynamic properties of different brain regions. The dynamical regime for a population of neurons generating oscillations in neural recordings can be discovered by stimulating the population and recording its subsequent response to stimulation. There are different dynamical regimes that can produce population-level neural oscillations. For certain dynamical regimes, like that of a nonlinear oscillator, the phase response curve (PRC) can help differentiate the dynamic state of the population. The PRC can be measured by stimulating the population across different phases of its oscillatory state. However, neural dynamics are non-stationary, so neural oscillations will vary in frequency and amplitude across a recording and the PRC can change over time. This non-stationarity could bias a PRC estimated from an electrophysiological experiment, preventing accurate characterization of a neural populations dynamics. This necessitates tools that can operate online to trigger stimulation and update PRC estimates. To that end, we develop online methods for tracking non-stationary oscillations and recovering PRCs corrupted by estimation errors. We validate the performance of our non-stationary oscillation estimator compared to both a known ground truth model and an alternative phase estimation approach. We demonstrate that a PRC can be recovered online underdifferent random error conditions in silico and that a similar amplitude response curve (ARC) can be estimated from physiologic data using online methods compared to offline approaches.

neuroscience↗

bioRxiv2024

Neural Decoding and Feature Selection Techniques for Closed-Loop Control of Defensive Behavior

ObjectiveMany psychiatric disorders involve excessive avoidant or defensive behavior, such as avoidance in anxiety and trauma disorders or defensive rituals in obsessive-compulsive disorders. Developing algorithms to predict these behaviors from local field potentials (LFPs) could serve as foundational technology for closed-loop control of such disorders. A significant challenge is identifying the LFP features that encode these defensive behaviors. ApproachWe analyzed LFP signals from the infralimbic cortex and basolateral amygdala of rats undergoing tone-shock conditioning and extinction, standard for investigating defensive behaviors. We utilized a comprehensive set of neuro-markers across spectral, temporal, and connectivity domains, employing SHapley Additive exPlanations for feature importance evaluation within Light Gradient-Boosting Machine models. Our goal was to decode three commonly studied avoidance/defensive behaviors: freezing, bar-press suppression, and motion (accelerometry), examining the impact of different features on decoding performance. Main resultsBand power and band power ratio between channels emerged as optimal features across sessions. High-gamma (80-150 Hz) power, power ratios, and inter-regional correlations were more informative than other bands that are more classically linked to defensive behaviors. Focusing on highly informative features enhanced performance. Across 4 recording sessions with 16 subjects, we achieved an average coefficient of determination of 0.5357 and 0.3476, and Pearson correlation coefficients of 0.7579 and 0.6092 for accelerometry jerk and bar press rate, respectively. Utilizing only the most informative features revealed differential encoding between accelerometry and bar press rate, with the former primarily through local spectral power and the latter via inter-regional connectivity. Our methodology demonstrated remarkably low time complexity, requiring <110 ms for training and <1 ms for inference. SignificanceOur results demonstrate the feasibility of accurately decoding defensive behaviors with minimal latency, using LFP features from neural circuits strongly linked to these behaviors. This methodology holds promise for real-time decoding to identify physiological targets in closed-loop psychiatric neuromodulation.

bioengineering↗

bioRxiv2024

Cross-species modeling and enhancement of cognitive control with striatal brain stimulation

Brain disorders, particularly mental disorders, might be effectively treated by direct electrical brain stimulation, but clinical progress requires understanding of therapeutic mechanisms. Animal models have not helped, because there are no direct animal models of mental illness. We show a path past this roadblock, by leveraging a common ingredient of most mental disorders: impaired cognitive control. We previously showed that deep brain stimulation (DBS) improves cognitive control in humans. We now reverse translate that result, showing that DBS-like stimulation of the mid-striatum improves cognitive control in rats. Using this model, we identify a mechanism, improvement in domain-general cognitive control, and rule out competing hypotheses such as impulsivity. The rat findings explain prior human results and have immediate implications for clinical practice and future trial design. One Sentence Summary: Developing a reliable animal model of a human brain stimulation therapy reveals that this therapy works by enhancing the brains ability to process conflicting pieces of evidence.

neuroscience↗

bioRxiv2023

Psychometric validation and clinical correlates of an experiential foraging task

Measuring the function of decision-making systems is a central goal of computational psychiatry. Individual measures of decisional function could be used to describe neurocognitive profiles that underpin psychopathology and offer insights into deficits that are shared across traditional diagnostic classes. However, there are few demonstrably reliable and mechanistically relevant metrics of decision making that can accurately capture the complex overlapping domains of cognition whilst also quantifying the heterogeneity of function between individuals. The WebSurf task is a reverse-translational human experiential foraging paradigm which indexes naturalistic and clinically relevant decision-making. To determine its potential clinical utility, we examined the psychometric properties and clinical correlates of behavioural parameters extracted from WebSurf in an initial exploratory experiment and a pre-registered validation experiment. Behaviour was stable over repeated administrations of the task, as were individual differences. The ability to measure decision making consistently supports the potential utility of the task in predicting an individuals propensity for response to psychiatric treatment, in evaluating clinical change during treatment, and in defining neurocognitive profiles that relate to psychopathology. Specific aspects of WebSurf behaviour also correlate with anhedonic and externalising symptoms. Importantly, these behavioural parameters may measure dimensions of psychological variance that are not captured by traditional rating scales. WebSurf and related paradigms might therefore be useful platforms for computational approaches to precision psychiatry.

neuroscience↗

bioRxiv2022

Bayesian methods for optimizing deep brain stimulation to enhance cognitive control

ObjectiveDeep brain stimulation (DBS) of the ventral internal capsule/striatum (VCVS) is a potentially effective treatment for several mental health disorders when conventional therapeutics fail. Its effectiveness, however, depends on correct programming to engage VCVS sub-circuits. VCVS programming is currently an iterative, time-consuming process, with weeks between setting changes and reliance on noisy, subjective self-reports. An objective measure of circuit engagement might allow individual settings to be tested in seconds to minutes, reducing the time to response and increasing patient and clinician confidence in the chosen settings. Here, we present an approach to measuring and optimizing that circuit engagement. ApproachWe leverage prior results showing that effective VCVS DBS engages circuits of cognitive control, that this engagement depends primarily on which contact(s) are activated, and that circuit engagement can be tracked through a state space modeling framework. We combine this framework with an adaptive optimizer to perform a principled exploration of electrode contacts and identify the contacts that maximally improve cognitive control. Main resultsUsing behavioral simulations directly derived from patient data, we show that an Upper Confidence Bound (UCB1) algorithm outperforms other optimizers (roughly 80% probability of convergence to a global optimum). SignificanceWe show that the optimization can converge even with lag between stimulation and effect, and that a complete optimization can be done in a clinically feasible timespan (a few hours). Further, the approach requires no specialized recording or imaging hardware, and thus could be a scalable path to expand the use of DBS in psychiatric and other non-motor applications.

bioengineering↗

bioRxiv2021

Quantifying defensive behavior and threat response through integrated headstage accelerometry

BackgroundDefensive and threat-related behaviors are common targets of investigation, because they model aspects of human mental illness. These behaviors are typically quantified by video recording and post hoc analysis. Those quantifications can be laborious and/or computationally intensive. Depending on the analysis method, the resulting measurements can be noisy or inaccurate. Other defensive behaviors, such as suppression of operant reward seeking, require extensive animal pre-training. New MethodWe demonstrate a method for quantifying defensive behavior (immobility or freezing) by 3-axis accelerometry integrated with an electrophysiology headstage. We tested multiple pre-processing and smoothing methods, and correlated them against two common methods for quantification: freezing as derived from standard video analysis, and suppression of operantly shaped bar pressing. We assessed these three methods ability to track defensive behavior during a standard threat conditioning and extinction paradigm. ResultsThe best approach to tracking defensive behavior from accelerometry was Gaussian filter smoothing of the first derivative (change score or jerk). Behavior scores from this method reproduced canonical conditioning and extinction curves at the group level. At the individual level, timepoint-to-timepoint correlations between accelerometry, video, and bar press metrics were statistically significant but modest (largest r=0.53, between accelerometry and bar press). Comparison with existing methodsThe integration with standard electrophysiology systems and relatively lightweight signal processing may make accelerometry particularly well suited to detect behavior in resource-constrained or real-time applications. At the same time, there were modest cross-correlations between all three methods for quantifying defensive behavior. ConclusionsAccelerometry analysis allows researchers already using electrophysiology to assess defensive behaviors without the need for additional behavioral measures or video. The similarities in behavioral tracking and modest correlations between each metric suggest that each measures a distinct aspect of defensive behavior. Accelerometry is a viable alternative to current defensive measurements, and its non-overlap with other metrics may allow a more sophisticated dissection of threat responses in future experiments. HighlightsO_LIA novel method to assess defensive behavior and immobility based on headstage accelerometry C_LIO_LICompatible with readily available, open-source neurophysiology systems C_LIO_LIProvides behavioral insights without the need for video analysis software and with relatively minimal processing, suitable for rapid closed-loop experiments C_LI

neuroscience↗

bioRxiv2021

Towards Biophysical Markers of Depression Vulnerability

A major difficulty with treating psychiatric disorders is their heterogeneity: different neural causes can lead to the same phenotype. To address this, we propose describing the underlying pathophysiology in terms of interpretable, biophysical parameters of a neural model derived from the electroencephalogram. We analyzed data from a small patient cohort of patients with depression and controls. We constructed biophysical models that describe neural dynamics in a cortical network activated during a task that is used to assess depression state. We show that biophysical model parameters are biomarkers, that is, variables that allow subtyping of depression at a biological level. They yield a low dimensional, interpretable feature space that allowed description of differences between individual patients with depressive symptoms. They capture internal heterogeneity/variance of depression state and achieve significantly better classification than commonly used EEG features. Our work is a proof of concept that a combination of biophysical models and machine learning may outperform earlier approaches based on classical statistics and raw brain data.

neuroscience↗

bioRxiv2021

Impact of stimulation location relative to grey and white matter on single pulse electrical stimulation responses in the human brain

BackgroundElectrical neuromodulation is an increasingly common therapy for a wide variety of neuropsychiatric diseases. Unfortunately, therapeutic efficacy is inconsistent, possibly a result of our limited understanding of the mechanisms and the massive stimulation parameter space. Objective/HypothesisTo better understand the role different parameters play in inducing a response, we systematically examined single pulse-induced cortico-cortico evoked potentials (CCEP) as a function of stimulation amplitude, duration and location in the brain and relative to grey and white matter. MethodsWe measured voltage peak amplitudes and area under the curve of intracranially recorded stimulation responses as a function of distance from the stimulation site, pulse width, current injected, location relative to grey and white matter, and brain region stimulated (N=52, n=719 stimulation sites). ResultsIncreasing stimulation pulse width increased response values near the stimulation location. Increasing stimulation amplitude (current) increased responses nonlinearly. Locally (<15 mm from the stimulation site), stimulation closer to the grey matter-white matter boundary induced larger responses. In contrast, for distant sites (>15 mm), white matter stimulation consistently produced larger responses than stimulation in or near grey matter. These relationships were different between cingulate, lateral prefrontal, and lateral temporal cortical stimulation. ConclusionThese results demonstrate the importance of location and stimulation parameters in inducing a specific output and indicate that a stronger local response may require stimulation in the grey-white boundary while stimulation in the white matter may be needed for network activation, suggesting that stimulation location can be tailored for a specific outcome, key to informed neuromodulatory therapy. HighlightsO_LIIntracranial single pulse electrical stimulation (SPES) response increases with increased pulse duration mostly near the stimulation site C_LIO_LISPES response varies nonlinearly with injected current with an effect of distance from the stimulation site. C_LIO_LISPES near the grey-white boundary and 90{degrees} to the nearest cortical axis induces larger local responses, but white matter stimulation produces larger distant responses. C_LIO_LIThe relationship between SPES location and responses depends on brain region stimulated C_LI

neuroscience↗